AI RESEARCH
Evaluating LLM-Generated Obfuscated XSS Payloads for Machine Learning-Based Detection
arXiv CS.LG
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ArXi:2604.19526v1 Announce Type: cross Cross-site scripting (XSS) remains a persistent web security vulnerability, especially because obfuscation can change the surface form of a malicious payload while preserving its behavior. These transformations make it difficult for traditional and machine learning-based detection systems to reliably identify attacks. Existing approaches for generating obfuscated payloads often emphasize syntactic diversity, but they do not always ensure that the generated samples remain behaviorally valid.